Implementing loglinear classification (without training), for CL classification

appengine/findit/libs/math/functions.py

 # Copyright 2016 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 
 class Function(object):
   """Base class for mathematical functions.
 
   The ``callable`` interface is sufficient for when you only ever need to
   invoke a function. But many times we want to have more information about
@@ skipping 26 matching lines @@
     """
     return self.__class__(lambda x: g(self(x)))
 
 
 class MemoizedFunction(Function):
   """A function which memoizes its value for all arguments."""
   def __init__(self, f):
     super(MemoizedFunction, self).__init__(f)
     self._memos = {}
 
-  def _ClearMemos(self):
+  def ClearMemos(self):
     """Discard all memoized results of this function."""
     self._memos = {}
 
   def __call__(self, x):
     try:
       return self._memos[x]
     except KeyError:
       fx = self._f(x)
       self._memos[x] = fx
       return fx